Operations | Monitoring | ITSM | DevOps | Cloud

Kepler and Insights: Built From Opposite Directions

Most companies buy AI tools for developers and hope the impact shows up somewhere. A faster sprint. Fewer escaped bugs. Something. What they don’t have is a way to actually see it happening, which means adoption becomes a leap of faith instead of a measured bet. That’s the gap Kepler and GitKraken Insights close together, and it’s worth understanding as one story, not two separate product updates.

Why Your Internet Is Slow: Is It Your Network, ISP, or Your Machine?

Someone on your team says "the Internet is slow." Twenty minutes later, IT finds out the Internet was never the problem. Maybe it was a laptop with a full RAM disk. Maybe it was an ISP outage two towns over that had nothing to do with your office. Misdiagnosing slow Internet wastes time. It sends you down the wrong fix path, like rebooting a router when the real issue is sitting on someone's desktop.

Introducing the next generation of the BigPanda AI Incident Assistant

Effective incident response depends on having all of the context surrounding what’s happening. You have to understand your systems, services, architecture, and teams deeply enough to correctly interpret whatever alert just fired. Too often, that context doesn’t arrive packaged neatly in one place. Gathering and interpreting context correctly under time pressure is one of the most difficult parts of the job.

How I Support Humans in the AI Era

When our company pushed everyone to start using AI tools, I thought about what it would mean for my team. As a remote company, we are already challenged by the lack of organic human connection. Every connection is planned and takes effort, and now, AI adds another layer. People now spend part of their day collaborating with a tool rather than with a person, which can take away from the time we spend learning from each other.

Kubernetes AI SRE Agent Finds a Crash Loop Nobody Asked About: AURA

You ask for a routine health check and expect a clean baseline. What came back was a pod that had restarted 788 times, unrelated to the question. AURA is connected to a Kubernetes cluster and to Prometheus through read-only MCP servers, running as one coordinator with two specialized workers. The prompt is one sentence: check the health of the cluster, and confirm whether all the pods are running. What comes back is not a baseline. AURA names the state as CrashLoopBackOff and attaches the restart count to it.

No Custom Adapter: AI SRE Agent AURA Debugs Product Catalog in Dash0

The platform shows you which service is failing and which paths it touches, and stops there. Point AURA at the same telemetry and the cause comes back too. Dash0 shows the product catalog service in a failed state across the selected window, with errors on the path from the frontend service.

KPI cards: build a reliability dashboard that doesn't force tradeoffs

This week's Feature Friday: Principal Product Manager Christine Byun walks through KPI cards, a new way to build custom dashboards in Engineering Intelligence. KPI cards pull key metrics, like change failure rate and rollback frequency, into compact tiles so they stay visible without taking up chart space. That means the metric you're actively working, incidents, in this demo, gets full-size room, without losing sight of the rest of your system.

Data Center: More or Less | SolarWinds TechPod

In this episode, Sean and Crystal explore the complex and rapidly evolving landscape of AI, data center impacts, regulation challenges, and societal implications. They discuss the urgency of establishing standards and the lessons from historical industrial revolutions to navigate AI's future responsibly.